Selective extraction,structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal

This article reports an extraction–purification of napins from an industrial rapeseed meal and the assessment of their antimicrobial activity against Fusarium langsethiae. The best extraction conditions are observed at pH 2, 12% (w/w) of rapeseed meal after 15 min of extraction in water at room temperature. Under these conditions the extraction is highly selective, allowing a simple purification process (ammonium sulfate precipitation followed by desalting size exclusion chromatography) to get purified napins. These napins possessed significant anti-Fusarium activity (IC₅₀ = 70 μM) and a compact secondary structure rich in α-helix, which may explain this bioactivity.     

Geopolymers based on a coarse low-purity kaolin mineral: Mechanical strength as a function of the chemical composition and temperature

A coarse mineral with 70% kaolinite and 30% quartz was calcined and chemically activated by alkaline solutions of Na₂SiO₃ and NaOH. The compressive strength evolution was investigated as a function of the curing temperature at 20 and 80 °C, and the molar ratios of SiO₂/Al₂O₃ (2.64-4.04) and Na₂O/Al₂O₃ (0.62-1.54). For curing at 20 °C, the best composition was SiO₂/Al₂O₃ = 2.96 and NaO/Al₂O₃ = 0.62, reaching 85 MPa at 28 days. Curing at 80 °C had a positive effect on the strength development only in the first 3 days. X-ray diffraction of the geopolymeric formulations showed the formation of amorphous silicoaluminates of similar nature. The microstructure consisted of unreacted quartz and metakaolinite particles in a matrix of silicoaluminate polymer and condensed silica gel from the unreacted sodium silicate.     

Analysis of complexity indices for classification problems: Cancer gene expression data

Currently, cancer diagnosis at a molecular level has been made possible through the analysis of gene expression data. More specifically, one usually uses machine learning (ML) techniques to build, from cancer gene expression data, automatic diagnosis models (classifiers). Cancer gene expression data often present some characteristics that can have a negative impact in the generalization ability of the classifiers generated. Some of these properties are data sparsity and an unbalanced class distribution. We investigate the results of a set of indices able to extract the intrinsic complexity information from the data. Such measures can be used to analyze, among other things, which particular characteristics of cancer gene expression data mostly impact the prediction ability of support vector machine classifiers. In this context, we also show that, by applying a proper feature selection procedure to the data, one can reduce the influence of those characteristics in the error rates of the classifiers induced.     

BPC – A binary priority countdown protocol

In modern wireless ad hoc networks, with a high speed PHY, every collision means a significant loss of useful bandwidth. In the last few years different binary contention protocols have been introduced to address this problem. In this work we propose a novel binary contention protocol called binary priority countdown (BPC) protocol, whose goal is to reduce collisions as well as contention time. BPC uses a new priority countdown mechanism which exploits the efficiency of binary countdown, but the priority countdown process is not constrained to a single binary countdown round. This way, the priority space is not defined by the length of binary countdown round, like in other binary countdown protocols proposed in the literature, and arbitrary medium access priorities can be decremented through multiple binary countdown rounds if necessary. The ability of a new priority countdown mechanism to count down any priority number without changing the length of a binary countdown round, allows independent management of priority space. This “independence” of priority space introduces new optimization and adaptation possibilities. Collision memory effect is recognized and described. BPC protocol reveals connection between unary, binary and digit contention protocols. All three groups of protocols can now be seen as members of the same class of contention algorithms. Preliminary simulation results are shown.     

Shear dispersion in dense granular flows

We formulate and solve a model problem of dispersion of dense granular materials in rapid shear flow down an incline. The effective dispersivity of the depth-averaged concentration of the dispersing powder is shown to vary as the Péclet number squared, as in classical Taylor–Aris dispersion of molecular solutes. An extension to generic shear profiles is presented, and possible applications to industrial and geological granular flows are noted.     

Stability of rigid blocks exposed to single-pulse excitation

This paper proposes a numerical procedure that can predict the minimum duration of a rectangular, half-cycle sine wave, linearly increasing and triangular single-pulse excitation required to overturn the rigid block resting on a moving base. Since the linearization assumption in the derivation of an analytical solution, which has already been used by Housner and other researchers, cannot be valid for a block with various slenderness ratios and dimensions, a derivation of numerical solutions which would be valid for all types of block is necessary. The proposed numerical procedure takes into account the possibility of sliding and uplifting of the block from the base. The numerical algorithm for the proposed numerical procedure in a commercial code C++ is given in the “Appendix.”